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Architecture-based conceptions of mind

In Peter Gardenfors, Katarzyna Kijania-Placek & Jan Wolenski (eds.), In the Scope of Logic, Methodology, and Philosophy of Science (Vol II). Kluwer Academic Publishers (2002)

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  1. [Letter from Gilbert Ryle].Gilbert Ryle - 1932 - Philosophy 7 (26):250 -.
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  • Intelligence without representation.Rodney A. Brooks - 1991 - Artificial Intelligence 47 (1--3):139-159.
    Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...)
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  • The Computer Revolution in Philosophy.Martin Atkinson & Aaron Sloman - 1980 - Philosophical Quarterly 30 (119):178.
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  • What is it like to be a bat?Thomas Nagel - 1974 - Philosophical Review 83 (October):435-50.
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  • The Concept of Mind.Gilbert Ryle - 1949 - Revue Philosophique de la France Et de l'Etranger 141:125-126.
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  • Towards a design-based analysis of emotional episodes.Ian Wright, Aaron Sloman & Luc P. Beaudoin - 1996 - Philosophy, Psychiatry, and Psychology 3 (2):101-126.
    he design-based approach is a methodology for investigating mechanisms capable of generating mental phenomena, whether introspectively or externally observed, and whether they occur in humans, other animals or robots. The study of designs satisfying requirements for autonomous agency can provide new deep theoretical insights at the information processing level of description of mental mechanisms. Designs for working systems (whether on paper or implemented on computers) can systematically explicate old explanatory concepts and generate new concepts that allow new and richer interpretations (...)
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  • The Principles of Linguistic Philosophy.J. E. Llewelyn - 1967 - Philosophical Quarterly 17 (66):77-79.
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  • Individuals: An Essay in Descriptive Metaphysics.James Cargile - 1959 - Journal of Symbolic Logic 38 (2):320-323.
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  • When physical systems realize functions.Matthias Scheutz - 1999 - Minds and Machines 9 (2):161-196.
    After briefly discussing the relevance of the notions computation and implementation for cognitive science, I summarize some of the problems that have been found in their most common interpretations. In particular, I argue that standard notions of computation together with a state-to-state correspondence view of implementation cannot overcome difficulties posed by Putnam's Realization Theorem and that, therefore, a different approach to implementation is required. The notion realization of a function, developed out of physical theories, is then introduced as a replacement (...)
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  • Physical symbol systems.Allen Newell - 1980 - Cognitive Science 4 (2):135-83.
    On the occasion of a first conference on Cognitive Science, it seems appropriate to review the basis of common understanding between the various disciplines. In my estimate, the most fundamental contribution so far of artificial intelligence and computer science to the joint enterprise of cognitive science has been the notion of a physical symbol system, i.e., the concept of a broad class of systems capable of having and manipulating symbols, yet realizable in the physical universe. The notion of symbol so (...)
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  • On automating diagrammatic proofs of arithmetic arguments.Mateja Jamnik, Alan Bundy & Ian Green - 1999 - Journal of Logic, Language and Information 8 (3):297-321.
    Theorems in automated theorem proving are usually proved by formal logical proofs. However, there is a subset of problems which humans can prove by the use of geometric operations on diagrams, so called diagrammatic proofs. Insight is often more clearly perceived in these proofs than in the corresponding algebraic proofs; they capture an intuitive notion of truthfulness that humans find easy to see and understand. We are investigating and automating such diagrammatic reasoning about mathematical theorems. Concrete, rather than general diagrams (...)
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  • The Ecological Approach to Visual Perception.Marc H. Bornstein - 1980 - Journal of Aesthetics and Art Criticism 39 (2):203-206.
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  • The Mentality of Apes.Wolfgang Khler - 1999 - Routledge.
    First Published in 1999. Routledge is an imprint of Taylor & Francis, an informa company.
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  • Unended Quest.Karl Raimund Popper - 1976 - New York: Fontana.
    A brilliant account of the life of one of the most influential thinkers of the twentieth century. Popper also explains some of the central ideas in his work, making this ideal reading for anyone coming to his life and work for the first time.
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  • The Conscious Mind: In Search of a Fundamental Theory (2nd edition).David J. Chalmers - 1996 - Oxford University Press.
    The book is an extended study of the problem of consciousness. After setting up the problem, I argue that reductive explanation of consciousness is impossible , and that if one takes consciousness seriously, one has to go beyond a strict materialist framework. In the second half of the book, I move toward a positive theory of consciousness with fundamental laws linking the physical and the experiential in a systematic way. Finally, I use the ideas and arguments developed earlier to defend (...)
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  • Descartes' Error: Emotion, Reason, and the Human Brain.Antonio R. Damasio - 1994 - Putnam.
    Linking the process of rational decision making to emotions, an award-winning scientist who has done extensive research with brain-damaged patients notes the dependence of thought processes on feelings and the body's survival-oriented regulators. 50,000 first printing.
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  • Semantics in an intelligent control system.A. Sloman - 1994 - Philosophical Transactions of the Royal Society: Physical Sciences and Engineering 349:43-58.
    Much research on intelligent systems has concentrated on low level mechanisms or sub-systems of restricted functionality. We need to understand how to put all the pieces together in an *architecture* for a complete agent with its own mind, driven by its own desires. A mind is a self-modifying control system, with a hierarchy of levels of control, and a different hierarchy of levels of implementation. AI needs to explore alternative control architectures and their implications for human, animal, and artificial minds. (...)
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  • Descartes’ error: Emotion, rationality and the human brain.Antonio Damasio - 1994 - New York: Putnam 352.
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  • The Missing Link: Implementation and Realization of Computations in Computer and Cognitive Science.Matthias Josef Scheutz - 1999 - Dissertation, Indiana University
    The notion of computation has attracted researchers from a wide range of areas, cognitive psychology being one of them. The analogy underlying the usage of "computer" in cognitive psychology can be succinctly summarized by saying that the mind is to the brain as the program is to the hardware. Two main assumptions are buried in this analogy: that the mind can somehow be understood computationally, and that the same kind of relation-the implementation relation-that obtains between programs and computer hardware obtains (...)
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  • The ``semantics'' of evolution: Trajectories and trade-offs in design space and niche space.Aaron Sloman - unknown
    This paper attempts to characterise a unifying overview of the practice of software engineers, AI designers, developers of evolutionary forms of computation, designers of adaptive systems, etc. The topic overlaps with theoretical biology, developmental psychology and perhaps some aspects of social theory. Just as much of theoretical computer science follows the lead of engineering intuitions and tries to formalise them, there are also some important emerging high level cross disciplinary ideas about natural information processing architectures and evolutionary mechanisms and that (...)
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  • Why robots will have emotions.Aaron Sloman & Monica Croucher - 1981
    Emotions involve complex processes produced by interactions between motives, beliefs, percepts, etc. E.g. real or imagined fulfilment or violation of a motive, or triggering of a 'motive-generator', can disturb processes produced by other motives. To understand emotions, therefore, we need to understand motives and the types of processes they can produce. This leads to a study of the global architecture of a mind. Some constraints on the evolution of minds are disussed. Types of motives and the processes they generate are (...)
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  • Actual possibilities.A. Sloman - unknown
    This is a philosophical `position paper' (html and pdf versions), starting from the observation that we have an intuitive grasp of a family of related concepts of ``possibility'', ``causation'' and ``constraint'' which we often use in thinking about complex mechanisms, and perhaps also in perceptual processes, which according to Gibson are primarily concerned with detecting positive and negative affordances, such as support, obstruction, graspability, etc. We are able to talk about, think about, and perceive possibilities, such as possible shapes, possible (...)
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